Forensic challenging samples are often characterized by severe DNA degradation, low endogenous DNA content, and insufficient sequencing depth, which limit both the genotyping performance and the informativeness of conventional STR-based approaches. Such samples are frequently encountered in scenarios including long-term burial and aged skeletal remains, where close relatives are often unavailable as reference samples and distant kinship inference therefore becomes particularly important. Low-coverage whole-genome sequencing (lcWGS) offers a promising opportunity for addressing this problem; however, most currently available kinship inference methods for lcWGS data originate from the ancient DNA field, and their applicability to degraded forensic samples remains insufficiently evaluated. This study aims to systematically compare multiple low-coverage kinship analysis tools in terms of their applicability and robustness for distant relationship inference under degraded forensic-sample conditions. Simulated pedigrees containing first- to seventh-degree relatives were generated based on Han Chinese populations from the 1000 Genomes Project. High-depth WGS data were downsampled to 0.01×-10×, and degraded datasets with varying fragment length distributions and damage patterns were simulated using Gargammel. Genotyping and imputation were performed using the 1240K, FIGG, and custom-selected highly polymorphic SNP panels. Based on these SNP panels, multiple kinship inference tools, including KING, Merlin, READ, ngsRelate, lcMLKin, ancIBD, IBIS, and KIN, were evaluated for their performance in inferring third- to seventh-degree relationships. The results revealed substantial variability in performance among different kinship inference tools. In addition, heat-degraded samples generated by high-temperature treatment of real pedigree samples and skeletal remains were incorporated into the study design to validate the practical applicability of the analytical strategy. This study provides a targeted lcWGS-based analytical framework for distant kinship inference in degraded forensic samples and offers methodological support for optimizing forensic genetic genealogy in investigative lead generation.

Authors

• Xiameng Chen (Department of Forensic Genetics, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, China)
• Ao Cheng (Department of Forensic Genetics, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, China)
• Jiaming Xue (Department of Forensic Genetics, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, China)
• Qiushuo Wu (Department of Forensic Genetics, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, China)
• Shengqiu Qu (Department of Forensic Genetics, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, China)
• Weibo Liang (Department of Forensic Genetics, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, China)